A VOC in water sensor · Web viewIn this paper we describe volatile organic compound (VOC) detection by a submersible photoionisation detection (PID ) sensor, which delivered broad

9th European Waste Water Management Conference 12-13 October 2015, Manchester, UK

A VOC IN WATER SENSORDean, F.W.H., Witty,A.D. and Stockdale, M.J.

Ion Science Ltd, UKCorresponding Author Email. [email protected]

Abstract

In this paper we describe volatile organic compound (VOC) detection by a submersible photoionisation detection (PID ) sensor, which delivered broad range sensitivity to most VOCs in air. The sensing components comprised a water repellent membrane overlaying a shallow photoionisation cavity, which included an electrodic means of adventitious water elimination therefrom.

The response of the sensor to various organics in potable water was compared with what might be predicted from equilibration of gas in the PID cavity and surrounding water according to Henry’s Law. Compounds such as alcohols for which the Henry’s Law constant kH is high, responded according to Henry’s Law, whereas low miscibility compounds were sensed at only a fraction of the expected equilibrated concentration.

The total, background response of the sensor to chlorinated tap water was typically equivalent to ~5-10 μg /L benzene, and was sufficiently invariant to enable the screening of water containing less than this concentration of benzene. It is thought that the background may be due in part to chloramines.

Keywords

benzene screening PID pollution sensor VOC volatile water

Introduction

Photoionisation detection (PID) was invented in the 1960’s (Lovelock 1963 and Lovelock et al.,1982), specifically to sense volatiles eluted in gas chromatography. Since then it has evolved into an increasingly field worthy technique, by virtue of more sensitive and temperature stable amplifiers, more resilient components, more stable electrical and electrochemical configurations, condensation resistance and miniaturisation (Stockdale and Eagling 2010, Dean and Stockdale 2006). We have modified a state of the art commercial PID air sensor to enable extended immersion in water, with particular attention to removal of any condensate generated underwater by means of a patented water electrolysing electrode.

The outstanding attribute of PID used in field environments is its rapid and broad range sensitivity to most volatiles. Remarkably, clean fresh air remote from sources of pollution commonly delivers a response equivalent to one or two hundred parts per billion (ppb v/v) equivalent of a typical VOC. Thus PID easily finds use as a ‘clean air’ detector in personnel safety, process safety and integrity and various screening applications.

Figure 1 illustrates the sensing mechanism in PID . (1), analytes passively diffuse through a porous membrane into a shallow cavity, where (2), they are exposed to radiation emitted from a PID high UV lamp window opposing the porous membrane. The radiation breaks up susceptible VOC molecules in the cavity into charged molecular fragments, known as photo-ions (3a). The electric current arising from ion collection at the cathode and anode in the PID cavity (3b) is amplified measured as a photoionisiation current.

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Other prospective sources of current arising in the cell, such as photoelectrons and electrolytic current flowing across the PID walls, are collected by an intervening third electrode. This also electrolyses incipient water condensation breaching the two outer electrodes, so that substantially, only a photocurrent flows and is measured, between the cathode and anode, from which the VOC concentration is calculated.

The most common PID UV source is a low pressure krypton electrodeless discharge lamp (‘PID Kr’), which releases ionising photons at 10.0 and 10.6 eV. According to their ionisation threshold energies, about 90% of common industrial VOC’s are photoionised by the 10.6 eV photons, and thus sensed. Notable is the high sensitivity to aromatics and unsaturated compounds; resolution below 1 part per billion (ppb) in a stable ambient atmosphere is achievable. Most single carbon compounds and saturated CFC’s, as well as acetylene, ethane and propane are not sensed by PID Kr.

The relative gaseous responsivities of PID Kr to specific VOC analytes are known to be invariant, and quoted as ‘sensitivity factors’ Sanalyte, relative to responsivity Rcal to a calibration gas at 298 K, enabling the gaseous concentration p of hundreds of analytes S to be determined from a PID response R on the basis of a single calibration:

p = S R / Rcal (i)

At low concentrations, a VOC chemically in equilibrium between water and a gaseous headspace establishes an equilibrium vapour pressure p (atm) according to Henry’s Law:

p = kH,cp ѳ exp[C(1/T - 1/Tѳ)] caq (ii)

where kHѳ (mol/(L.atm)) is the Henry’s Law constant at standard temperature (25 oC), T (K, oC

+273.15) is the ambient temperature, C is the Henry’s Law temperature coefficient, and caq (mol/L) is the aqueous concentration of the volatile.

The PID probe in water is shown schematically in Figure 2. Water ingress into the PID containing cradle was prevented by means of an intervening hydrophobic membrane. Since volatile analyte consumption by a PID sensor is slow, and the PID cavity was very shallow, the PID in water sensor is anticipated to deliver rapid and substantially complete equilibration of a volatile between the gas sensing cavity and surrounding aqueous solution. This prospectively enables a PID in water sensor to be used to estimate the concentration of a specified VOC analyte in water on the basis of a single calibration. Combining (i) and (ii):

caq, measured = (1 / kH,cpѳ ) exp[C(1/Tѳ - 1/T)] SR / Rcal (iii)

In the discussion below we refer to percentage equilibration Ѳ, which relates the concentration of caq calculated from the sensor response and (iii) to the actual concentration:

Ѳ = caq, measured / caq (iv)

The variation of Ѳ with analyte, flow rate, temperature and aqueous concentration are all discussed below.

Experimental method

A PID in water probe, of some 45 mm diameter, is shown in Figure 3. It incorporate specially adapted commercial PID sensors (miniPID, Ion Science Ltd). The sensors include a detachable stack, Figure 4-5. The electrode stack, with its filter, were seated in the sensor body by means of flexible clips.




The co-parallel stack electrodes, separated by PTFE spacers, were slatted to enable ionising light emanating from the Kr lamp abutting the ‘front’ electrode to penetrate the stack. The opposing ‘back’ electrode was abutted by a porous PTFE filter, which was friction welded to the PID housing to minimise leak paths that would otherwise degrade the response.

The assembly was in turn seated in a submersible cradle, to which it was sealed by means of adhesive around the stack’s filter perimeter. The sensor included six pins providing power, 26 x gain adjustment, light oon/off control, sensor output and water electrolysing electrode output. On the adjoining sensor interface board the signals were converted to digital outputs communicable via USB cable to a computer. The probe was operated via software on the computer, enabling control of PID pulsing, gain and data acquisition as well as aqueous PID calibration. The whole assembly weighed less than 200 g, enabling full portability.

Routine sensor measurement in air was carried out by sequential presentation of 100 mbar.L.min-1 ultrahigh purity (UHP) air (Air Products, UK) and 2 ppm isobutylene in air (SIP Analytical UK, certified grade) via a bronze gas cradle. The probe gas response to other volatiles was also measured to compare against the corresponding volatile in water response, by stepwise syringe addition of the volatile to a 124 L glass sphere containing agitated air sourced from a ventilated laboratory.

All volatiles used in this work were of >99% purity (Sigma Chemicals, UK, ‘Analytical grade’). Tap water and commercial still or sparkling ‘spring’ water was variously engaged as specified below.

A known volume of 1 to 1.5 L water was placed in columnar flasks of 10 cm diameter. In most experiments water was drawn straight from the tap and typically heated in a microwave to one or two oC above ambient, being the temperature established on the stirrer platform on which the flask was placed, containing a 28 mm magnetic flea. Water was added and in some experiments sparged with UHP air. The submersible PID was then placed in the flask to within 1 to 2 cm of the flea. The flask was then sealed with a modified lid.

In experiments with less soluble volatiles a stock aqueous solution was prepared immediately before the experiment. Volatile liquids were added stepwise to the flask via gas tight syringe (Hamilton, USA).

Results and discussion

Response in air

The linearity in gaseous response to benzene of the PID in water sensor is shown in Figure 6 at ambient and 100% humidity. The 90% response time to benzene in air was approximately 10 s, incuding the time required for gas volatilisation and mixing. The electrode stack used shows higher non-linearity than is typical of state of the art PID sensors. It was primarily engaged in this work concerning the lower sensitivity limit of PID in water.

Effect of agitation.

Flea rotation of some 18 Hz was found to deliver a flow invariant response from water containing benzene, toluene, PCE, p-xylene, and ethanol as shown in Figure 7. This flow rate was maintained in subsequent experiments. Note the response is least flow dependent for ethanol, which was the most soluble volatile tested.

Responsivity.




The performance of the PID in water probe is presented in Table 1 together with solubility data. Of particular note is the very high responsivity and hence resolution obtained for benzene.

This is shown more explicitly in Figure 8 for small additions of benzene to fresh tap water. The high sensitivity of the probe to benzene, and other aromatics can be anticipated from high PID in air responses to aromatics,S, and low kH values. That is to say, equilibrated aromatic vapour pressure that is relatively high in the gas phase. Resolution is calculated from 3σ variation in 0.5 Hz noise, (~0.4 mV), typically obtained with clean tap water, and expressed as an equivalent concentration of the volatile.

An interesting trend moving down Table 1 was the decreasing analyte pressure equilibration within the PID, Ѳ, for analytes of decreasing solubility kH. This is difficult to explain. For low solubility analytes, the maximum rate of volatilisation of analyte entering the PID cavity may well be comparable to the rate of photo-destruction of the analyte therein, and therefore the latter may influence both the response time and the extent of equilibration Ѳ. For a highly sensed compound Typically, photoionisation current in a PID is sufficient to ionise every analyte molecule in a hypothetically sealed PID cavity within a few seconds. Of course, the formation of non-ionisable products is not the inevitable consequence of photo-ion formation and neutralisation at an electrode. However, progressive oxidation is likely upon both analyte photo-excitation, whether it be to form ions or excited molecules.

Table 1: Characteristic sensor performance attributes for a selection of volatiles. S, the sensitivity of the Kr-PID to the VOC in air vs isobutylene (Dean and Hagg 2015). Henry’s Law kH and C data was obtained from Sander 2015. The extent of gas partitioning measured in the PID cavity relative to that expected from equation (iv), Ѳ, was temperature and concentration dependent.

Volatile S kH C t5% , s t90% , s resolution, ug/L

Ѳ, %

Ethanol 0.11 190 6600 ~1 12 750 100%1-propanol 0.21 130 7500 3 40 600 85%2-propanol 0.23 120 7500 3 20 500 100%

1-butanol 0.25 130 7200 6 30 350 100%Benzene 2.0 0.16 4100 5 130 0.4 50%Toluene 2.1 0.15 4000 7 360 0.7 30%

Xylene 3.6 0.13 3800 8 660 1.8 12%

TCE 2.3 0.1 4700 16 1100 0.9 15%

PCE 1.4 0.059 4700 18 >1200 0.8 15%

Response time

Table 1 also shows characteristic response times of the sensor to volatiles. t5% and t90% are respectively the times required for 5 and 90% response to a step change in volatile concentration. Interestingly, t5% response times do not vary widely. They possibly reflect volatile inter-diffusion through air in the PID membrane at rates dependent upon their respective molecular weights, and not their highly variable Henry’s Law constant. The t90% response times vary far more widely. Some modelled responses are shown in Figure 9.




The model is based upon parallel capacitor charging behaviour:

R = Aexp(-at) + (1-A)exp(-bt) (v)

The close fit provided by the model suggests two time dependent processes, the slower of which may relate to infilling of gaseous voids behind the PID sensor cavity.

Concentration.

Figure 10 shows the dependence of response on benzene concentration in tap water. The wide dynamic range of measurement is an intrinsic feature of PID. Typical of a low solubility volatiles, θ increased with concentration. Since this behaviour was apparent in the non-linear region of the high sensitivity electrode stack engaged, Figure 6, the experiment was repeated with a wider range stack. The effect was the same. This phenomenon is the subject of further investigation.

Effect of temperature

Henry’s Law constants are very sensitive to temperature and hence the PID response to volatiles in water is also highly temperature dependent, as shown in Figure 11. Irrespective of their solubility, volatile partial pressures double every ~10 oC. This was an important consideration in the PID probe’s design.

Field performance attributes.

Research to date has indicated that the PID probe described herein is serviceable in water for several weeks. It is very likely, as with conventional PID in air, that a PID sensor’s calibration depends upon the photolytic generation of ozone in air inside the PID cavity to keep the PID’s light emitting window face clean. Thu we expect loss of calibration is a possible issue for the PID in water probe to be engaged in oxygen free environment. Preliminary tests confirm this is not a concern for intermittent monitoring of water samples. We have also verified that silty, salty and other aqueous constituents had less than 2% affect on the response to water other than what might be expected from volumetric dilution of the volatile, and in the case of salt, from a small salting out effect. Saturation of water with carbon dioxide decreased the standard and high sensitivity stack PID response to all volatiles by about 50%, as is the case in volatile response measurements in ambient CO2 vs air.

Conclusions

1. A robust PID in air probe has been developed for under water measurement of organic volatiles.

2. The probe exhibited broad range responsivity to volatiles. Reponse and resolution were circumscribed by their solubility, and PID in moist air response.

3. Low solubility volatiles showed a shortfall in response as compared to what Henry’s Law partitioning between the vapour and aqueous phase.




Figure 1: Schematic of PID sensor, showing sensing narrative 1-3.

Figure 2: Schematic of amphibious PID probe.




Figure 3: PID in water probe.

Figure 4: PID pellet and lamp sub-assembly during engagement to sensor body.




A B

Figure 5: A tilted view of the PID electrode stacks showing electrode layers. The lamp seat is 6 mm diameter. A: high sensitivity electrode stack used in most of this work. B: standard stack.

Figure 6: Linearity PID in water probe to benzene in air, engaging a high sensitivity electrode stack, Figure 5 B.


Figure 2. Schematic of PID in water sensor.



Figure 7: Effect of stirrer rate on response, expressed as fraction of the expected response assuming sensor response according to Henry’s Law, Ѳ. Arrows indicate measurement sequence.

Figure 8: Response of PID in water probe to stepwise additions of benzene to tap water.




Figure 9: Measured and modelled responses to stepwise additions of disparate analytes isopropanol and trichloroethylene.

Figure 10: Effect of step increased benzene concentration in water caq on response R and measurement equilibration factor Ѳ. In determining Ѳ, caq was adjusted for cell non-linearity, and kH adjusted for small changes in temperature.




Figure 11: The effect of temperature on predicted and measured vapour pressure. Ethanol, 790 mg/L. p-xylene 0.36 mg/L

Acknowledgements

Ron Fink, Ion Science Ltd is thanked for his contributions to mechanical design.

References

Dean FWH & Haag WG n.d., Search by chemical compound, Available from http://www.ionscience.com/#home-nav-01=tab3 [28 Sept 2015]

Dean FWH & Stockdale, MJ 2006, Ionisation devices, US Patent 7,046,012

Lovelock JE, Shoemake GR & Zlatis, A 1963, ‘Sensitive Ionisation Cross-Section Detector for Ion Chromatography’, Analytical Chem, 35(4) 460-465.

Lovelock, JE 1982, ‘Ultrasensitive Chemical Detectors’, Applied Atomic Collision Physics, 5, 1-30.

Sander, R, 2015 ‘Compilation of Henry’s law constants (version 4.0) for water as solvent’, Atmos.Chem. and Physics, 15 4399-4981

Stockdale, MJ and Eagling KM 2010, Electrode contact assembly and associated photoionisation detector assembly, US Patent 7,821,270.’



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A VOC in water sensor · Web viewIn this paper we describe volatile organic compound (VOC) detection by a submersible photoionisation detection (PID ) sensor, which delivered broad